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The problem of joint estimation of power spectrum and modulation from realizations of frequency modulated stationary wideband signals is considered. The study is motivated by some specific signal clas...
We study the problem of corrupted sensing, a generalization of compressed sensing in which one aims to recover a signal from a collection of corrupted or unreliable measurements. While an arbitrary si...
his paper describes a time-series-based classification approach to identify similarities between bio-medical-based situations. The proposed approach allows classifying collections of time-series repre...
Standard compressive sensing results state that to exactly recover an s sparse signal in R^p, one requires O(s\cdotlog p) measurements. While this bound is extremely useful in practice, often real wor...
This paper proposes a new fBm (fractional Brownian motion) interpolation/reconstruction method from partially known samples based on CS (Compressive Sampling). Since 1/f property implies power law ...
The main hurdle in the realization of dynamic spectrum access (DSA) systems from physical layer perspective is the reliable sensing of low power licensed users. One such scenario shows up in the unlic...
One of the key challenges in sensor networks is the extraction of information by fusing data from a multitude of distinct, but possibly unreliable sensors. Recovering information from the maximum numb...
Statistical properties of double-auction markets with Bid-Ask spread in market order are investigated through the response function. We first attempt to utilize the so-called Madhavan-Richardson-Rooma...
We consider a diffusion (t)t0 with some T -periodic time dependent input term contained in the drift: under an unknown parameter # 2 , some discontinuity – an additional periodic signal – occurs at...
The optimal reconstruction of cosmic metric perturbations and other signals requires knowledge of their power spectra and other parameters. If these are not known a priori, they have to be measured ...
Singular Spectrum Analysis and many other subspace-based methods of signal processing are implicitly relying on the assumption of close prox- imity of unperturbed and perturbed signal subspaces extr...
We consider the problem of recovering of continuous multi-dimensional functions f from the noisy observations over the regular grid m−1Zd, m ∈ N∗. Our focus is at the adaptive estimation...
Higher Criticism is a method for detecting signals that are both sparse and weak. Although first proposed in cases where the noise variables are independent, Higher Criticism also has reasonable per...
The detection and estimation of signals in noisy, limited data is a problem of interest to many scientific and engineering communities. We present a mathematically justifiable, computationally simple,...

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